Research Status of Online Course Teaching in Application-Oriented Universities in China

Author(s):  
Li Bingbing ◽  
Zhou Xiaofen ◽  
Liu Zili
2020 ◽  
Vol 72 (2) ◽  
Author(s):  
Tomasz Dzieńkowski ◽  
Marcin Wołoszyn ◽  
Iwona Florkiewicz ◽  
Radosław Dobrowolski ◽  
Jan Rodzik ◽  
...  

The article discusses the results of the latest interdisciplinary research of Czermno stronghold and its immediate surroundings. The site is mentioned in chroniclers’ entries referring to the stronghold Cherven’ (Tale of Bygone Years, first mention under the year 981) and the so-called Cherven’ Towns. Given the scarcity of written records regarding the history of today’s Eastern Poland, Ukraine, and Belarus in the 10th and 11th centuries, recent archaeological research, supported by geoenvironmental analyses and absolute dating, brought a significant qualitative change. In 2014 and 2015, the remains of the oldest rampart of the stronghold were uncovered for the first time. A series of radiocarbon datings allows us to refer the erection of the stronghold to the second half/late 10th century. The results of several years’ interdisciplinary research (2012-2020) introduce qualitatively new data to the issue of the Cherven’ Towns, which both change current considerations and confirm the extraordinary research potential in the archeology of the discussed region.


2012 ◽  
Vol 16 (3) ◽  
Author(s):  
Laurie P Dringus

This essay is written to present a prospective stance on how learning analytics, as a core evaluative approach, must help instructors uncover the important trends and evidence of quality learner data in the online course. A critique is presented of strategic and tactical issues of learning analytics. The approach to the critique is taken through the lens of questioning the current status of applying learning analytics to online courses. The goal of the discussion is twofold: (1) to inform online learning practitioners (e.g., instructors and administrators) of the potential of learning analytics in online courses and (2) to broaden discussion in the research community about the advancement of learning analytics in online learning. In recognizing the full potential of formalizing big data in online coures, the community must address this issue also in the context of the potentially "harmful" application of learning analytics.


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